0299 Effect of Glycemic Extremes on Sleep/wake and Alzheimer’s Disease Pathophysiology
Bibliographic record
Abstract
Type 2 diabetes increases the risk of developing Alzheimer’s disease by 2-4-fold. Further, sleep disruption is characteristic of both Alzheimer’s disease and metabolic dysfunction. It remains unclear, however, how alterations in peripheral and brain metabolism alter pathology and, ultimately, impact the sleep/wake cycle. The goal of this study, therefore, was to elucidate how the brain regulates metabolism in euglycemic conditions, as well as when challenged with hyper- and hypoglycemic conditions, with the hypothesis that altered glucose homeostasis and sleep dysregulation may be leading to accelerated disease progression. Biosensors were implanted bilaterally into the hippocampus of APP/PS1 mice, a model of amyloid-beta (Aβ) overexpression, to measure ISF fluctuations in glucose, glutamate, and lactate. These were paired with cortical EEG and EMG recordings for simultaneous sleep/wake analysis. To examine the effect of glycemic extremes on the brain’s metabolic profile and arousal state, the mice were challenged with a 2g/kg IP injection of glucose, a 1mg/kg IP injection of glibenclamide, a KATP channel antagonist, as well as a .5U/kg injection of insulin. Both hyper- and hypoglycemic challenges result in significant increases in arousal in 3-month old, wildtype mice. This increased arousal matched the increases in ISF lactate, indicating an increase in overall neuronal activity. However, in an aged APP/PS1 model mouse, the metabolic response to glycemic challenges was muted and there was seemingly no impact on arousal state, which is likely due to an increase in the overall amount of time spent awake. This finding is consistent with previous data demonstrating progressive age and pathology-dependent increases in arousal time. This study represents a novel approach to understanding the interactions between sleep, cerebral metabolism, and Alzheimer’s Disease progression. The results show both glycemic extremes and Alzheimer’s Disease pathophysiology can cause increased arousal, which is known to further contribute to metabolic dysregulation, accelerate amyloid-beta and tau deposition and neurodegeneration, suggesting a cyclic relationship between sleep and disease pathology. Harold and Mary Eagle Fund for Alzheimer’s Research, NIH/NIA 1K01AG050719, New Vision Award through Donors Cure Foundation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".